The role of prefrontal cortex in task switching

Eric Denovellis

November 23, 2015

“Each of the objects and events we encounter in the environment affords a range of possible actions in response to it. The appropriate response varies as a function of the task
— Rogers & Monsell (1995)

Rule / Task Set

What determines appropriate response?

Explicit Goals or Intention

OR

Context and Learned Rules (Internal states)

+

Environmental stimuli

=

Appropriate Response

Cognitive Demand: The monitoring and allocation of control

Adjustments in control can occur rapidly. Reaction time and accuracy tend to change:

  • After errors
  • Repeating the same task
  • When switching between tasks
  • When responding to stimuli with more than response associated with them

Cognitive Demand: The monitoring and allocation of control

Prefrontal Cortex is important for monitoring and allocation of control

  • Perseverative behavior after injury
  • Task responsive neurons

Dynamics

Functional Organization of the Prefrontal Cortex

The problem of the ACC

Mixed selectivity

Outline

  • Task Switching Paradigm
  • Aim #1: LFP Analysis
  • Aim #2: Single Neuron and Population Analysis
  • NEW Aim #3: Tools for multi-dimensional investigation of electrophyisological datasets
  • Status of the Project

Task Switching Paradigm

Task Switching Paradigm

Task Switching Paradigm

Task Switching Paradigm

Factors that Affect the Amount of Attention Needed

  • Errors in previous trials
  • Stimulus Congruency
  • Number of Rule Repetitions

Aim #1

Rule-dependent networks in dlPFC

Analysis of ACC and dlPFC-ACC Synchrony

Aim #2

Motivation for Aim #2 and Aim #3

Tools for Investigating Multi-dimensional Models

SFN Poster Analysis and Problems

Proposed Corrections at Qualifying Exam

Current State: Proposed models

Aim #3

Interactive Visualizations

WHY: Statistical summaries can be misleading

(Visualizations help us check our assumptions)

WHY: We are collecting more data

  • More data → more complex theories → more comparisons
  • Multidimensional data requires multiple views and summaries to fully understand
  • Harder to display all the data on a single static figure
  • Examining raw data becomes more difficult

“…to convey the richness of the data stories we are telling rather than simplifying them”

Interactive visualizations can help us quickly make comparisons and deal with complexity

Heer & Shneiderman (2012)
Heer & Shneiderman (2012)

Dynamic visualizations, when combined with interactivity, can help us understand complex data by preserving relationships between data

Web-enabled visualizations are familiar, easily shareable, and enable analysis transparency

RasterVis

Demo

SpectraVis

Demo

glmVis

Demo

Linking visualizations together to explore datasets

Summary and Conclusion